This study presents a new instrument called a low-cost albedometer (LCA)
composed of two illuminance sensors that are used to measure in situ
incident and reflected illuminance values on a daily timescale. The ratio
between reflected vs. incident illuminances is called the albedo index and can be compared with actual albedo values. Due to the shape of the
sensor, the direct radiation for zenith angles ranging from 55 to 90∘
is not measured. The spectral response of the LCA varies with the solar
irradiance wavelengths within the range 0.26 to 1.195 µm, and the
LCA detects 85 % of the total spectral solar irradiance for clear sky
conditions. We first consider the theoretical results obtained for 10
different ice and snow surfaces with clear sky and cloudy sky incident solar
irradiance that show that the LCA spectral response may be responsible for an
overestimation of the theoretical albedo values by roughly 9 % at most.
Then, the LCA values are compared with two “traditional” albedometers, which are CM3
pyranometers (Kipp & Zonen), in the shortwave
domain from 0.305 to 2.800 µm over a 1-year measurement period
(2013) for two sites in a tropical mountainous catchment in Bolivia. One site
is located on the Zongo Glacier (i.e., snow and ice surfaces) and the second
one is found on the crest of the lateral moraine (bare soil and snow
surfaces), which present a horizontal surface and a sky view factor of 0.98.
The results, at daily time steps (256 days), given by the LCA are in good
agreement with the classic albedo measurements taken with pyranometers with
R2=0.83 (RMSD = 0.10) and R2=0.92 (RMSD = 0.08) for the
Zongo Glacier and the right-hand side lateral moraine, respectively. This
demonstrates that our system performs well and thus provides relevant
opportunities to document spatiotemporal changes in the surface albedo from
direct observations at the scale of an entire catchment at a low cost.
Finally, during the period from September 2015 to June 2016, direct
observations were collected with 15 LCAs on the Zongo Glacier and
successfully compared with LANDSAT images showing the surface conditions of
the glacier (i.e., snow or ice). This comparison illustrates the
efficiency of this system to monitor the daily time step changes in the
snow and ice coverage distributed on the glacier. Despite the limits imposed by
the angle view restrictions, the LCA can be used between 45∘ N and
45∘ S during the ablation season (spring and summer) when the melt
rate related to the albedo is the most important.

Albedo is a key variable controlling the surface energy balance through the
shortwave radiation budget. Documenting the spatiotemporal changes in this
variable is a major concern in hydrological modeling, particularly in
mountainous regions where the seasonal snow and glacier covers induce
significant and rapid changes in the surface state with subsequent impacts
on the energy budget. Hereafter, the spectral albedo is defined as the ratio
between the amount of energy reflected by the surface and the incident
energy for each wavelength of the solar spectrum (between 0.3 and
2.5 µm),
and the broadband albedo is the integration of the spectral
albedo weighted by the incident energy over the entire solar spectrum
(0.3-2.5 µm). The amount of shortwave radiation absorbed by the
surface depends on the spectral and angular distribution of the incident
shortwave radiation and the surface characteristics, both of which are
highly variable in space and time (Stroeve et al., 1997; Klok et al., 2003). Clouds
alter the angular and spectral properties of the incident radiation. With
respect to the snow and ice surfaces, the albedo in the visible wavelength
depends on the snow and ice properties, the impurity amount (e.g., black
carbon, dust, algae, etc.), and the snow depth for the shallow snowpack. In
the infrared portion of the spectrum, the albedo is mainly controlled by the
snow microstructure and is moderately sensitive to the solar zenith angle
(Warren, 1982). Liquid water and land have relatively low albedos (roughly
0.1 to 0.4), while snow and ice have higher albedos that can typically reach
0.9 for fresh snow. It is still challenging to measure the temporal and
spatial changes in the surface albedo from the scale of specific points up
to a regional scale. Different methods are commonly used to retrieve albedo
values from satellite images, ground photographs, or point measurements with
pyranometers. Satellite-derived albedo maps provide spatially continuous
datasets but are limited to clear sky conditions; these maps may contain
significant uncertainties, especially over complex topographies (Stroeve
et al., 1997; Klok et al., 2003; Dumont et al., 2012), and provide averaged data over a pixel
size of hundreds of square meters. Ground photography using pairs of
photographs in the visible and infrared wavelengths is used to collect
albedo maps that have a higher spatial resolution than satellite images but
which are limited by cloudy conditions, the possible masking of the relief,
an irregular grid due to the projection, and more complex ortho-rectification
processes in mountainous regions (e.g., Corripio, 2004; Dumont et al., 2011).
Finally, direct in situ snow and ice albedo measurements are sparse, relatively
expensive, often discontinuous, and may contain large uncertainties if the
sensor is not regularly checked (Sicart et al., 2001; van den Broeke et al., 2004).

A study published by Brock et al. (2000) aimed to document the spatial and
temporal variations of surface albedo on the Haut Glacier d'Arolla,
Switzerland during the 1993 and 1994 ablation seasons (from mid-May to
the end of August). They used a traditional Kipp & Zonen CM7B albedometer
(that is expensive) and relied on the temporal variations of albedo with
surface conditions as snow depth, surface snow density, and surface snow
grain size. One of their conclusions underlined the importance of conducting
in situ field measurements continuously at a daily timescale across a glacier
throughout the ablation season, as the measurements are crucial to developing
albedo parameterization into hydro-glaciological models.

This article analyzes the efficiency of a low-cost albedometer (hereafter
called LCA) that measures the time series of in situ incident and reflected
illuminance values that are used to calculate an accurate proxy of the
albedo values called the albedo index. The illuminance is the total luminous flux
incident on a surface per unit area. It is a measure of how much the
incident light illuminates the surface, wavelength-weighted by the
luminosity function to correlate with the human perception of brightness. In
Sect. 2, we present the characteristics of and uncertainties in the LCA
measurements along with a comparison with the theoretical values for 10
different ice and snow states and for two different incident irradiance
spectra (cloudy or clear sky). Then, Sect. 3 presents two experiments
carried out on a high-altitude tropical mountain site in Bolivia (Zongo
glacierized catchment). A first application for punctual in situ measurements
validates the LCA in the field via a comparison with traditional radiometers
for two contrasting surfaces: snow and ice on the glacier or snow and bare soil on
the moraine. After that, a second application on the same glacier documents
the snow–ice changes on the surface of the glacier during the period that
extends from September 2015 to June 2016.

Table 1Characteristics of the HOBO® Pendant
Temperature/Light Data Logger as per the manufacturer.

The LCA is comprised of two HOBO® Pendant
Temperature/Light Data Loggers: one for the incident illuminance and the
other for the reflected illuminance (Fig. 1). The sensor characteristics are
given in Table 1. This sensor measures the illuminance in lux and the
measurement range is between 0 and 320 000 lux. The lux quantifies the light
incident flux per unit area. One lux equals one lumen per square meter with
a uniform distribution. In photometry, this unit is used as a measure of the
intensity of the light hitting or passing through a surface as perceived by
the human eye. The illuminance may be related to an energy quantified in
watts per square meter (W m−2), but the conversion factor differs
depending on the wavelength considered according to the luminosity function,
a standardized model of the human visual perception of brightness. As a
consequence, the illuminance depends on the spectral distribution of the
incident light. Due to its operating temperature range (see Table 1), the
use of the LCA is limited at very cold locations where the temperature continuously falls
below −20 ∘C for long periods of time. However, this
may not be too critical since the main purpose of the device is to document
albedo surface changes during melt periods when such low temperature
conditions are not typical.

Figure 2HOBO® Pendant
Temperature/Light Data Logger and CM3 responses as a function of the wavelength
and two examples of total solar irradiances for a clear sky (in blue) and for a
cloudy sky (in purple) given by the DISORT model (Stamnes et al., 1988; W m−2µm−1).

The spectral range of the HOBO® Pendant
Temperature/Light Data Logger is 0.26 to 1.195 µm (see Fig. 2). The
spectral response of the sensor represents the amount of incoming signal
recorded by the sensor for any given wavelength and is reported in Fig. 2.
This figure shows that the spectral response of the sensor increases from 20
to 100 % between 0.26 and 0.915 µm and then decreases until the
upper limit of the sensor sensitivity (i.e.. 1.195 µm). The sensor
detects roughly 85 % of the total solar irradiance for clear sky
conditions (Fig. 2). Laboratory tests conducted with a goniometer showed
that the HOBO® Pendant Temperature/Light Data
Logger cannot measure the irradiance for incident zenith angles ranging from
55 to 90∘ (±2∘, where 0∘ is
the vertical illumination). This is due to the design of the sensor (Fig. 1c).
Traditionally, the in situ albedo is measured using a CM3 pyranometer (Kipp
& Zonen) in the shortwave domain from 0.305
to 2.800 µm (Fig. 1b). The CM3 is part of the CNR1/CNR4 net
radiometer, which is intended for the analysis of the radiation balance of
solar and thermal infrared radiation. The design of the CM3 is such that the
upward-facing and downward-facing sensors measure the energy received from
the entire hemisphere (a field of view of almost 180 degrees). The output is
expressed in W m−2. The CM3 sensor has a 100 % response for
wavelengths between 0.305 and 2.8 µm (Fig. 2).

Figure 3Semi-infinite diffuse beam albedo of pure ice as a function
of the effective air bubble radius (mm) with a constant effective bubble
concentration ne′=0.3 mm−3. Here 0.3 mm−3
is the mean bubble concentration determined from 28 Greenland and Antarctica
ice core samples (Gardner and Sharp, 2010); the semi-infinite diffuse beam albedo
of dusty and pure snow is from DISORT modeling with or without dust
and with a specific surface area (SSA) equal to 40 or 5 m2 kg−1
(Stamnes et al., 1988; Carmagnola et al., 2013). The red line shows the LCA response in percent.

It is noteworthy that the LCA contains an internal memory; this is not the
case for the CM3 pyranometers, which need to be connected to an external
module for data acquisition programming and data storage. The LCA cannot
provide direct access to the albedo as its response is not constant
depending on the wavelength in the solar spectrum. Finally, the conversion
from illuminance to radiation in W m−2 is not straightforward
since it depends on the spectral distribution of the incident and reflected
light.

Figure 3 shows 10 simulated spectral albedo curves for different glacier
surfaces: 4 for snow (with dusty or pure snow and with a specific surface
area (SSA) equal to 5 or 40 m2 kg−1) and 6 for ice with
different bubble concentrations (see Gardner and Sharp, 2010, for details).
These 10 different surface types are used below to calculate the theoretical
uncertainty of the LCA measurements.

In the visible domain, the spectral albedo of pure snow is high (0.95) and
the albedo decreases in the infrared towards 0.1 for longer wavelengths
(1.5–2 µm; Fig. 3). For dusty snow, the spectral albedo is lower
than for pure snow. To calculate the uncertainty for the ice covers, we
chose pure ice that only contains air bubbles and no impurity taken from the
study of Gardner and Sharp (2010). In this case, all of the photon
absorption events will occur within the ice and all of the scattering will
occur at the ice–bubble boundaries, thereby neglecting all surface
reflection as well as internal scattering and absorption by the interstitial
air (Mullen and Warren, 1988; Warren et al., 2002).

Two types of incident radiation are tested (clear sky and cloudy conditions
given by the SBDART model for the tropical Zongo latitude at 5000 m a.s.l.,
23∘ solar zenith angle, 0.1 atmospheric optical depth; see
Richiazzi et al., 1998, for details concerning the model). The cloudy
conditions are fully overcast with an optical depth of 64.

The theoretical broadband albedo and LCA albedo indexes are calculated over the
0.205–3.9 µm range using the theoretical solar irradiance, the LCA spectral
response from Fig. 2, and the semi-infinite diffuse beam albedo from
Fig. 3. The total incident radiation flux for LCA, Sinc (in W m−2),
is obtained by summing the theoretical incident radiation fluxes,
Sinc-th(λ) (in W m−2µm−1), weighted by the LCA
response, Rλ(−), at each spectral increment of 5.10−3µm
for both cloudy and clear sky conditions (Eq. 1).

(1)Sinc=∑λ=0.2053.9Sinc-thλRλdλ

Similarly, the reflected radiation flux for the LCA, Sref (in W m−2),
is obtained by summing the theoretical reflected radiation
fluxes, Sref-th(λ) (in W m−2µm−1), weighted
by the LCA response, Rλ(-), at each spectral increment of 5 µm
for each snow or ice class considered (Eq. 2).

(2)Sref=∑λ=0.2053.9Sref-thλRλdλ

Then, the LCA albedo index, Albedoindex (-), is the ratio between the reflected and incident
LCA radiation fluxes for each type of snow and ice surface and for cloudy or
clear sky conditions (Eq. 3).

(3)Albedoindex=SrefSinc

Finally, this LCA albedo index is compared with the theoretical broadband albedo when we
consider the spectral variations. Note that the results are presented with
the incoming radiation corresponding to the total solar irradiances for
clear sky and cloudy sky conditions and without testing the effect of the
angular limitation of the LCA.

Figure 4 compares the theoretical albedos and the LCA albedo index with the theoretical
perfect albedo for the 10 surface configurations and for clear and cloudy
skies. Slight differences exist for ice with a bubble radius between 0.02
and 0.2 mm with an underestimation of the LCA by 4 % for a clear sky. For
ice with an air bubble radius of 0.4 or 0.7 mm and for the two snow types
(dusty and pure), the LCA tends to overestimate the albedo by 8 % on
average for clear sky conditions. The LCA tends to overestimate for albedo
values higher than 0.5 (typically for snow) and to underestimate for low
values (i.e., for ice). A better agreement between the theoretical albedos
and the LCA albedo index is given in the cloudy case with an overall underestimation of
5 % compared with 9 % for the clear sky case. This is explained by the
response of the LCA based on the wavelength, which is null for the 1.20–2.30 µm
range (see Fig. 2).

Figure 5Study site with the Zongo Glacier and the location of the
meteorological stations: ORE (5050 m a.s.l.) outside of the glacier and SAMA
(5056 m a.s.l.) on the glacier. The numbers indicate the position of each
in situ LCA on ablation stakes.

The Zongo Glacier (16∘15′ S, 68∘10′ W)
is located in the Bolivian Cordillera Real (Fig. 5) between the Altiplano
Plateau in the west and the Amazon Basin in the east. In 2006, the glacier
covered an area of 1.96 km2 extending from 6100 to 4900 m a.s.l.
(Rabatel et al., 2012). For the whole glacier, the main precipitation type is
solid and the albedo increases after each snowfall with a snow line that
could reach the front of the glacier. After that, during dry consecutive
days the snow line rises up due to the snow melting processes. The Bolivian
Cordillera Real is located in the outer tropical zone, which forms a
transition zone between the tropics (continuously humid conditions) and the
subtropics (dry conditions). The climate of the outer tropics is
characterized by low seasonal temperature variability, high solar radiation
influx all year round, and marked seasonal humidity and precipitation. The
hydrological year (from 1 September to 31 August) can be
divided into three periods: (1) September–December, with a progressive
increase in moisture and precipitation; (2) January–April, which is the
core period of the rainy season (approximately two-thirds of the total
annual precipitation); and (3) May–August, when dry conditions prevail
(e.g., Sicart et al., 2011). However, precipitation can also occur during the dry
period due to Southern Hemisphere midlatitude disturbances that track much
further north of their usual path (e.g., Vuille and Ammann, 1997; Sicart et al., 2016).

Two contrasting sites with different characteristics were chosen in order to
evaluate the efficiency of the LCA (Fig. 5). These two sites belong to the
GLACIOCLIM observatory (https://glacioclim.osug.fr/, last access: 15 March 2018), which has maintained a
permanent glacio-meteo-hydrological monitoring program on the Zongo Glacier
since 1991 (Rabatel et al., 2013). The SAMA station is an automatic weather
station (AWS) located on the Zongo Glacier (Figs. 1, 5) and the ORE
station is a similar AWS located on the crest of the lateral moraine. In
order to capture the sky view for each station, ORE and SAMA, a digital
elevation model (DEM) at 30 m resolution taken from ASTER images (Tachikawa
et al., 2011) was used. The sky view factor, which is the fraction of the
celestial hemisphere visible from the surface defined by the local slope,
was calculated with the SAGA GIS software (System for Automated
Geoscientific Analyses, version 2.0.8) using the code provided by Boehner
and Antonic (2009). The sky view factors obtained are 0.92 and 0.98 for the
SAMA and ORE stations, respectively.

Figure 6(a) Comparison of the daily measured albedo at the ORE
site using the CNR1 radiometer and the LCA for the period from 7 November 2012
to 6 March 2013; daily data calculated from 11:00 to 15:00; RMSD = 0.1; n = 247. (b)
Comparison of the daily measured albedo at the SAMA site on the Zongo Glacier using
the CM3 sensor and LCA for the period from 1 December 2012 to 9 October 2013; daily
data calculated from 11:00 to 15:00; RMSD = 0.08; n= 175.
The red dots are for cloudy conditions and the white dots are for sunny
conditions, as per the classification given by Sicart et al. (2016). The
calculated regression lines are shown in red for cloudy conditions, blue
for sunny conditions, and black for all conditions. The dotted lines
represent the bisectors.

Considering the limited field of view of the
HOBO® Pendant Temperature/Light Data Logger, daily albedo values are
calculated between 11:00 and 15:00 local time, ensuring that direct
solar irradiance is caught by the two sensors. The albedo index is calculated in two
steps: (i) the sum of the hourly data for the incident illuminance and the
reflected illuminance between 11:00 and 15:00 and (ii) the calculation
of the daily albedo index by dividing the sum of reflected values by the sum of incident
illuminance values. The time series used for the ORE and SAMA stations are
7 November 2012–6 March 2013 and 1 December 2012–9 October 2013, respectively. Figure 6a and
b show the comparison between the CM3 albedo and LCA albedo indexes for the daily values
that range between 0.15 (dirty ice or bare soil) and 0.95 (fresh snow).

At the ORE site (Fig. 6a), two groups of points can be distinguished. The
lower group (albedo close to 0.25) corresponds to measurements over bare
soil. For the second group, the broadband albedo and albedo indexes range from 0.3 to 0.9,
corresponding to several snow cover conditions: (i) thin and dirty snow;
(ii) homogeneous fresh snow; and (iii) patchy snow covers. There is good
agreement between the CM3 broadband albedos and LCA broadband albedo indexes
(R2=0.90 and RMSD = 0.08, with 256 days). The distribution for the
albedos at the SAMA site (Fig. 6b) is more homogeneous. For the SAMA site,
the albedo variations are due to surface changes from ice to fresh snow. At
this second site, there is also good agreement between the CM3 and LCA
albedo (R2=0.93 and RMSD = 0.08, with 256 days).

The measurements are separated into two groups according to the sky
conditions, cloudy or sunny, as per the classification provided by
Sicart et al. (2016). If we consider the theoretical results from Sect. 2, the LCA
should give better results for cloudy conditions; however, there are not
enough measurements for clear sky conditions compared with the number of
measurements for cloudy conditions to be able to come to a conclusion. In
both cases, the LCA tends to slightly overestimate the albedo values by
5 %. This result is in good agreement with the theoretical results
presented in Sect. 2 (Fig. 4), showing that the LCA tends to overestimate
the theoretical albedo values for ice with bubbles and snow by less than
10 %. The results are in good agreement with the theoretical results
obtained in Sect. 2, with an overestimation for the high albedos and an
underestimation for the low albedos.

Figure 7Comparison between the LCA measurements and the 23
LANDSAT images (from 18 October 2015 to 30 June 2016, the numbers for the x axis
are the image numbers; see Table 2 for the correspondence) for the 15 points
on the Zongo Glacier (see Fig. 5 for the locations of the LCA). The red
points represent the albedo index value calculated with the LCA and the
grey bars indicate the surface state for the corresponding pixel (1: ice
and 2: snow). A value of 1.5 was chosen for stake number 14 as the pixel
showed patchy snow cover.

After the comparison between the CM3 and LCA, a second field experiment was
carried out in order to determine the spatiotemporal variability of the
snow cover on the Zongo Glacier during the period from 21 September 2015 to
30 June 2016. Fifteen LCA stations were installed on ablation stakes
distributed in the lower and middle part of the glacier at altitudes ranging
between 4929 and 5184 m a.s.l. (Fig. 5). In order to evaluate whether the
LCA provides coherent information on the spatiotemporal changes in the
surface state of the glacier (fresh snow, old snow, ice), we compared the
LCA data with information retrieved from the LANDSAT images. With regards to
the LANDSAT images (30 m resolution), we first selected, within the archive,
the cloud-free images recorded within the period when the LCA data were
available (a list of the 23 images used here is provided in Table 2). On the
LANDSAT images, we used a spectral band combination involving green,
near-infrared (NIR), and middle infrared (MIR) wavelengths (spectral bands
2, 4, and 5 for LANDSAT images 5 and 7), which are used to make a clear
differentiation between snow and ice surfaces (Rabatel et al., 2012). Then,
according to the values in the NIR and MIR bands, the pixels where the LCA
are located were classified as snow covered (value of 2 in Fig. 7) or ice
covered (value of 1 in Fig. 7). In one case, the chosen value was 1.5 as
the pixel showed patchy snow cover. This can be explained if we consider
that the spatial resolution of the LANDSAT is equal to 900 m2 and the
surface view by the sensor is less than 1 m2.

Figure 8Daily albedo index for the 15 LCA stations during the
period from 21 September 2015 to 30 June 2016. In yellow: missing data; binary
values considering the separation between ice (1: in black) and snow
(2: in grey) with a threshold equal to 0.39. In red: the daily precipitation
amount measured by the GEONOR rain gauge at the ORE station (mm day−1).

The LCA network was deployed in the lower and middle part of the Zongo
Glacier (Fig. 5), which is the zone where the snow line altitude goes up or
down depending on the snowfall events and ablation processes. For all of the
points, we identified a first period (18 October 2015 to 11 November 2015) with high
albedo values between 0.40 and 0.92. These values are in agreement
with the surface state of the glacier on the LANDSAT images in which the pixels
of the glacier tongue are all snow covered. During the second period, the
glacier surface is covered by ice or by snow depending on the altitude. In
further detail, we identified three groups organized by altitude ranges
depending on the changes in the surface state of the glacier with a first
group in the lower part of the glacier (LCA numbers 1, 2, 3, 4, 5), a second
group in the middle part of the glacier (LCA numbers 6, 7, 8, 9, 10, 11, 12),
and a third group with LCA numbers 13, 14, and 15 (see Fig. 5 for the
location). Finally, the comparisons between the in situ LCA measurements and the
surface state given by the LANDSAT images were used to visually identify a
threshold for the albedo index equal to 0.39 between snow and ice. These results are in
agreement with those obtained by Sicart et al. (2001), which showed that the albedo
for the Zongo Glacier ranges from 0.3 for dirty ice to 0.9 for fresh snow.
Using this threshold, it is possible to plot the evolution of the glacier
cover (even ice or snow) over time for different altitudes ranging from
4929 to 5184 m a.s.l. (Fig. 8).

Figure 8 gives the evolution of the albedo for the 15 points during the
period 21 September 2015–30 June 2016 and the precipitation amount measured by
a GEONOR precipitation gauge at the ORE station (Fig. 5). We can clearly
identify the snowfall events and see how the snow disappears, thus leaving
the glacier ice exposed. As a result, the snow line altitude variations can
be defined and vary between 4929 and 5184 m a.s.l. depending on the period
of the year. In further detail, it can be noted that at the beginning of the
study period (i.e., between September and November), the snow line quickly
rises up and goes down due to intermittent precipitation events. Then,
during the rainy season (from December to March), the glacier is mostly
snow covered (mainly above 5000 m a.s.l.). Finally, during the dry season
(April to June), the snow line rises up to 5150 m a.s.l. and the glacier
tongue is mainly snow free.

In this study we developed, evaluated, and tested a new low-cost albedometer
(LCA) comprised of two HOBO® Pendant
Temperature/Light Data Loggers measuring downward and upward illuminances.
The measurements of the field of view of the LCA in the laboratory with a
goniometer showed that the LCA cannot capture the radiation for zenith
angles ranging from 55 to 90∘ (±2∘).
The angle of view of the sensor is 55∘, which limits where and
when it can be used. To determine these limits, we calculated what the solar
angle is at noon for different latitudes throughout the year. Considering
the LCA is operational when the solar angle is greater than 55∘ at
noon, it may be used all year long at latitudes between 12∘ N and
12∘ S, from March to October between 12 and
30∘ N, and from September to March between 12 and
30∘ S. The sensor cannot be used at latitudes higher than
60∘ N or 60∘ S at any time throughout the year. Between
45∘ N and 45∘ S the sensors can be operated during the
ablation season when the glacier surface changes are the most important.
Using the LCA spectral response (0.205 to 1.2 µm), we evaluated the
simulated albedo index of the LCA over different types of snow and ice surfaces. The
results showed that the LCA albedo indexes are within −4 to +8 % of the
theoretical broadband albedo values, while considering that cloudy or clear
sky incident irradiances only account for the spectral response of the
LCA and not for the angular response of the LCA with respect to the ideal
response. In the second part of the study, we evaluated the LCA albedo indexes in the
field using CM3 broadband albedo values at two different sites on a tropical
mountain in Bolivia: on the Zongo Glacier, at one station located on the
glacier and another one located on the moraine. Data were recorded at hourly
time steps and then the albedo indices were calculated on a daily timescale
(from 11:00 to 15:00). The daily albedo indexes from the LCA are in good agreement
with the broadband albedo values derived from the CM3 pyranometer. By
comparing the LCA albedo estimates with the CM3 broadband albedo over a
period of approximately 260 days at the two sites, we conclude that the
efficiency of the albedo indexes given by the LCA is ±0.1 compared with classic CNR1
sensors. Future applications are certainly possible, especially considering
the low cost, the autonomy of the LCA in terms of energy, and the very small
size of the sensors. For example, the LCA could be useful to spatialize in situ
albedos in glacierized catchments both on the glacier, where the evolution
of the snow cover can be monitored, and in the non-glacierized part for the
evolution of the seasonal snow cover and, more generally, the changes in the
ground albedo due to, for example, variations in the soil moisture (Gascoin
et al., 2009). The comparison between the LCA measurements and LANDSAT images
during the period extending from 18 October 2015 to 30 June 2016 showed that the
LCA is a powerful tool that can be used to quantify the evolution of the
albedo index and characterize the surface state of the glacier by distinguishing
between fresh snow, dirty snow, and ice. In order to have good results for
the albedo index calculated with the LCA, a certain degree of caution is required: for
example, snow particles should not stay on the sensor and the sensor must be
kept horizontal. Therefore, we recommend a frequency of about 15 days
between each field visit and data download. This new system has demonstrated
its usefulness for a tropical glacier, and future studies in other climatic
contexts should be conducted.

This study was funded by the French Institut de Recherche pour le Développement
(IRD) through the Andean part of the
French glacier observatory service, GLACIOCLIM
(http://www-lgge.ujf-grenoble.fr/ServiceObs/SiteWebAndes/index.htm, last access: 2 May 2018), and was
carried out within the framework of the International Joint Laboratory
GREAT-ICE, a joint initiative of the IRD as well as universities and
institutions in Bolivia, Peru, Ecuador, and Colombia. All of the contributing
authors acknowledge the contribution of LABEX OSUG@2020, ANR grant no.
ANR-10-LABX-56. The Pléiades satellite image used for Fig. 1 was
obtained from the CNES-ISIS FC18473 program funded by the BIOTHAW project
(AAP-SCEN-2011-II). The authors would like to thank everyone who
participated in the field campaigns: Patrick Ginot, Maxime Harter, and Pierre
Vincent. We thank Sara Mullin and Lance Brooks for the correction of the English
text in a previous version of the paper.

Gardner, A. S. and Sharp, M. J.: A review of snow and ice albedo and the
development of a new physically based broadband albedo parameterization,
J. Geophys. Res., 115, F01009, https://doi.org/10.1029/2009JF001444, 2010.

This study presents a new instrument called a low-cost albedometer (LCA) composed of two illuminance sensors. The ratio between reflected vs. incident illuminances is called the albedo index and can be compared with actual albedo values. We demonstrate that our system performs well and thus provides relevant opportunities to document spatiotemporal changes in the surface albedo from direct observations at the scale of an entire catchment at a low cost.

This study presents a new instrument called a low-cost albedometer (LCA) composed of two...